The latest articles on DEV Community by fresed (@fresed). https://dev.to/fresed https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3817609%2F8fb92eb1-5a21-4dec-ae9a-86c602690635.png https://dev.to/fresed en fresed Wed, 11 Mar 2026 00:48:00 +0000 https://dev.to/fresed/fagent-memory-first-ai-agent-runtime-for-long-running-interrupted-workflows-ng5 https://dev.to/fresed/fagent-memory-first-ai-agent-runtime-for-long-running-interrupted-workflows-ng5 <p>Hi everyone! 👋 </p> <p>I’m a beginner developer fascinated by AI, neural networks, and agents. I built <strong>fagent</strong>, a memory-first AI agent runtime, because I noticed that most agent runtimes handle short tasks well, but struggle with <strong>long-running or interrupted workflows</strong>. Agents often forget context, previous decisions, or dependencies once you restart them. </p> <p><strong>What makes fagent different:</strong></p> <ul> <li> <strong>Layered memory</strong> – multiple memory types (file, vector, graph, task/workflow) working together. </li> <li> <strong>Graph-based recall</strong> – retrieve not just text, but the relationships between tasks, blockers, and decisions. </li> <li> <strong>Workflow repair</strong> – a helper layer to fix broken task flows without restarting everything. </li> <li> <strong>Multi-channel runtime</strong> – works via CLI, terminal, and messaging platforms. </li> <li> <strong>Local Graph UI</strong> – inspect memory and task graphs visually. </li> </ul> <p>fagent is open-source and available here: <a href="https://github.com/fresed05/fagent" rel="noopener noreferrer">https://github.com/fresed05/fagent</a></p> <p>I’d love your feedback on: </p> <ul> <li>How useful graph-based memory is compared to vector-only memory. </li> <li>How intuitive the workflow inspection UX feels. </li> <li>Any real-world workflows where you’d try a memory-focused agent. </li> </ul> <p>I’m excited to see how the community experiments with long-running agents. Let me know what you think, or if you have suggestions for improvements! </p> <p>Thanks for reading! 🚀</p> ai opensource rag agents